Research on Computation Model and Key Parameters of AIRS Supervised Classification in Remote Sensing Images

Author

Wu Yundong ; Geng Lichuan

Author_Institution

Coll. of Sci., Jimei Univ., Amoy, China

Volume

3

fYear

2009

fDate

4-5 July 2009

Firstpage

474

Lastpage

477

Abstract

A framework of remote sensing images classification based on Artificial Immune Recognition System (AIRS) is present in this papers. The relation between key parameters and the classification results are analyzed. As shown in the experiment results, the new framework inherits robustness of AIRS relative to key parameter. Experimental results show that this framework is better than Maximum Likelihood Classification method.

Keywords

artificial immune systems; geophysical techniques; geophysics computing; image classification; pattern recognition; remote sensing; AIRS supervised classification framework; Artificial Immune Recognition System; computation model; image classification; key parameters; remote sensing; Artificial immune systems; Classification algorithms; Computational modeling; Educational institutions; Image classification; Image recognition; Immune system; Maximum likelihood detection; Remote sensing; Robustness; AIRS; AIS; Remote Sensing Image; Supervised Classification;

fLanguage

English

Publisher

ieee

Conference_Titel

Environmental Science and Information Application Technology, 2009. ESIAT 2009. International Conference on

Conference_Location

Wuhan

Print_ISBN

978-0-7695-3682-8

Type

conf

DOI

10.1109/ESIAT.2009.441

Filename

5199734